Systems and methods for profile-based service recommendations

Abstract

Systems and methods for performing profile-based recommendations including receiving a user input from a user, extracting a query from the user input, identifying at least one category based on the user input, generating a user profile representative of the query and preferences of the user, retrieving data corresponding to services in the identified at least one category from a data source and generating a service profile for each respective service, determining a match between the user profile and the service profiles, generating, in response to the query, an output dataset corresponding to one or more service profiles in the at least one category determined from the matching. The services corresponding to at least one of services of a third party service provider, a location, and an objective.

What is claimed is: 
     
         1 . A method comprising:
 receiving, at a computing device in a network, a user input from a user;   extracting, by the computing device, a query from the user input;   identifying, by the computing device, at least one category based on the user input;   generating, by the computing device, a user profile representative of the query and preferences of the user;   retrieving, by the computing device, data corresponding to services in the identified at least one category from a data source and generating a service profile for each respective service;   determining, by the computing device, a match between the user profile and the service profiles; and   generating, by the computing device in response to the query, an output dataset corresponding to one or more service profiles in the at least one category determined from the matching.   
     
     
         2 . The method of  claim 1 , wherein generating the user profile representative of the query and the preferences of the user further comprises:
 retrieving, by the computing device, the user profile including the preferences of the user from a first data store; and   refining, by the computing device, the extracted query with the preferences of the user;   wherein the extracted query is representative of a defined objective of the user.   
     
     
         3 . The method of  claim 2 , further comprising:
 determining, by a machine learning model, a first set of embeddings representative of the user profile,   extracting, by the computing device, a second set of embeddings representative of a respective service profile, and   applying, by the computing device, a distance metric to determine a match between the user profile and the respective service profile.   
     
     
         4 . The method of  claim 3 , wherein the distance metric is a similarity score calculated for the user profile and the service profiles based on respective embeddings. 
     
     
         5 . The method of  claim 2 , wherein retrieving the data corresponding to the services of the identified at least one category from the data source further comprises:
 determining, by the computing device, a status of the retrieved data,   wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data.   
     
     
         6 . The method of  claim 1 , wherein the services correspond to at least one of services of a third party service provider, a location, and an objective. 
     
     
         7 . The method of  claim 1 , wherein the user input corresponds to a request for services in the category. 
     
     
         8 . The method of  claim 1 , wherein the data source is located in one or more other networks. 
     
     
         9 . A system comprising:
 a processor; and   a non-transitory computer readable media having stored thereon instructions that are executable by the processor to perform operations comprising:
 receive a user input from a user; 
 extract a query from the user input; 
 retrieve a user profile including preferences of the user; 
 refine the extracted query with the preferences of the user; 
 retrieve data corresponding to services in an identified category from a data source and generating a service profile for each respective service; 
 determine a match between the user profile and the service profiles; and 
 generate, in response to the query, an output dataset corresponding to one or more service profiles in the identified category determined from the matching; 
 wherein the extracted query is representative of a defined objective of the user. 
   
     
     
         10 . The system of  claim 9 , wherein refining the extracted query with the preferences of the user comprises:
 determine a first set of embeddings representative of the user profile;   determine a second set of embeddings representative of a respective service profile, and   apply a distance metric to determine a match between the user profile and the respective service profile,   wherein the distance metric is a similarity score calculated for the user profile and the service profiles based on respective embeddings.   
     
     
         11 . The system of  claim 10 , wherein retrieving the data corresponding to the services of the identified category from the data source further comprises:
 determine a status of the retrieved data,   wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data.   
     
     
         12 . The system of  claim 10 , wherein the services correspond to at least one of services of a third party service provider, a location, and an objective. 
     
     
         13 . The system of  claim 9 , wherein the user input corresponds to a request for services in the category. 
     
     
         14 . The system of  claim 9 , wherein the data source comprises one or more other networks. 
     
     
         15 . A non-transitory computer readable media having stored thereon instructions that are executable by a system to perform operations comprising:
 receive a user input from a user;   extract a query from the user input;   identify at least one category based on the user input;   determine a first set of embeddings representative of a user profile including preferences of the user and the query;   retrieve data corresponding to services in the identified at least one category from a data source and generating a service profile for each respective service; and   determine a match between the user profile and the service profiles.   
     
     
         16 . The non-transitory computer readable media of  claim 15 , wherein the instructions executable by the system further comprises:
 extract a second set of embeddings representative of a respective service profile, and   apply a distance metric to determine a match between the user profile and the respective service profile.   
     
     
         17 . The non-transitory computer readable media of  claim 16 , wherein the distance metric is a similarity score calculated for the user profile and the service profiles based on respective embeddings. 
     
     
         18 . The non-transitory computer readable media of  claim 16 , wherein the instructions executable by the system further comprises:
 obtain the data corresponding to the services in the identified at least one category from one or more other networks, and   store the service profiles in the identified at least one category in a data store.   
     
     
         19 . The non-transitory computer readable media of  claim 18 , wherein the instructions executable by the system further comprises:
 determine a status of the data corresponding to the services;   update the service profiles in the data store in response to determining the status exceeds a threshold value; and   wherein the status is determined based on timestamp data representative of a most recent update to the data,   wherein the data store is in a network of the system.   
     
     
         20 . The non-transitory computer readable media of  claim 15 , wherein the services correspond to at least one of services of a third party service provider, a location, and an objective.